What do digital intermediaries do?

Multiple technologies underpin the growth of digital intermediaries The digital economy has grown rapidly in recent years. Deloitte (2015b) valued the Australian digital economy at 5.9 per cent of GDP in 2015, up from 3.6 per cent of GDP in 2011 and expected to grow to 7.3 per cent by 2020. Continued development and use of internet platforms, social media and mobile apps are expected to be important drivers of growth.

The rise of digital intermediaries has been supported by progressive improvements in communications technologies, such as the internet, home and office computers, and mobile devices over the last several decades (Deloitte Access Economics 2015b). This reduces the cost of sending and receiving communications, and allows the transmission of digital products. More recently, other technologies such as data storage in the cloud, ‘big-data’

analytics, and machine learning are expanding the scope of functions that digital intermediaries provide. For example, iTunes offers their customers the option of storing all their music remotely in the cloud, to be streamed on any connected device as needed (Apple 2016).

The functions of digital intermediaries

The functions of digital intermediaries are varied, but can be roughly categorised as

‘matching’, ‘analysis and sorting’, and adding product value. Any one intermediary can provide one, some, or all of these services.

Matching market participants

Digital intermediaries, and the platforms they operate, help match market participants and lower search costs. For firms seeking inputs or customers, and consumers seeking final products, sorting through available products and services is a costly process requiring time, money and other resources. Rarely are such searches exhaustive.

Digital intermediaries help participants find better matches by lowering the cost of search.

One way is through collating and cataloguing all (or a portion of) agents in one place, which facilitates comparison of product offerings. But digital intermediaries may also offer:

• filtering or re-ordering offerings in a systematic way, such that the user can better distinguish between possible matches

• allowing ‘intent casting’, where the platform allows the user to describe their specific need (intent) to other users of the platform

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• aggregating results from multiple platforms in the one place, enabling easy comparison before routing the user to a specific supplier’s platform for purchase (Riemer et al. 2015).

Lowering search costs improves welfare by reducing the amount of resources expended on search, improving the quality of matches, and by encouraging new entrants into a market (or creating markets) where previously it was too costly for market participants to transact (Bakos 1998) (box B.2).

Box B.2 Matching platforms

Airbnb is a website where people can list, find and book accommodation. In particular, the platform has greatly reduced the cost of searching for, connecting and transacting with private, non-professional accommodation providers, rapidly expanding this market.

Skyscanner is a ‘meta-search’ website for flights and other travel services that aggregates and filters results from multiple platforms and distribution channels. Skyscanner does not process transactions itself, but rather channels consumers to the appropriate site.

Sources: Airbnb (2016); Riemer et al. (2015); Skyscanner (2016).

Data analysis and overcoming information asymmetry

Digital intermediaries can collect vast amounts of data, which can be used to both improve the quality of searches on their platform and offer new services that help overcome market inefficiencies (Riemer et al. 2015). Examples of data collected include producer listings, consumer feedback and reviews, and customer transaction data (Mangalindan 2012).

One way matches are improved is through ranking and recommending. Information asymmetry is a feature in most markets, with the producer having better information than the consumer. For example, it is difficult to know the quality of an accommodation provider prior to booking, in particular for small, non-branded providers. These asymmetries mean that simply cataloguing and filtering possible options in a neutral way may not result in an efficient match. A digital intermediary can use algorithms to rank products and services based on quality or other criteria or provide individualised searches based upon a consumer’s taste or needs (Riemer et al. 2015). These are then presented to the customer in a structured way, often as an ordered list. This can have an effect on how consumer perceive search results, with research showing that users trust and choose higher-ranked results more than lower-ranked results (Epstein and Robertson 2015). Such discrimination could be for a fee, for example, a supplier paying for their ad to be shown at the top of a list. Ideally, ranking and recommending provides a way to guide users towards a better match, while rewarding high-quality providers who receive the best feedback from consumers (Riemer et al. 2015). However, it could mislead consumers if it reflects providers who pay extra to promote their listing to the top of the list and this is not disclosed. Either way, ‘AAA plumbing’ is no longer enough to ensure your company is seen first.

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Box B.3 Review platforms

Review platforms are sites, sections of sites or applications that publish reviews (generally in the form of ratings or comments) on a range of goods and services. Reviews are mostly generated by ‘everyday consumers’ who have experienced or purchased the product, as opposed to specialist reviewers with intricate product knowledge.

Review platforms have expanded the opportunity for consumers to access independent information about a product. Prior to the internet, independent reviews were largely restricted to specialist reviewers who mostly focused on expensive goods and services (for example, cars or high-end restaurants) and for many products consumers were limited to the views and recommendations of family and friends. With online review platforms, the low cost of both publishing and accessing reviews enables many more independent reviews to be written on a wider variety of goods and services, including goods and services located overseas. Consumer reviews can now easily be found on small local restaurants, home goods, books, movies and tourism companies, to name but a few.

Sources: ACCC (2013); Luca and Zervas (2015); Segal (2011).

Ranking and recommending products requires a lot of information, both about the product and the customer. Digital intermediaries achieve this not by going out and assessing products themselves, but by encouraging platform participants to share information (box B.3). Some examples include TripAdvisor and Amazon (box B.4).

Independent recommendations are seen as a trustworthy source of information — consumers’ trust of online reviews ranks second only to recommendations from people they know (Nielsen 2009). The sentiments expressed in online reviews can therefore have a noticeable impact on a business’s bottom line. One study found that a one-star increase on Yelp (a restaurant review website) leads to a 5 to 9 per cent increase in revenue. The increase in revenue was higher for restaurants that are unbranded or not affiliated with a chain (Luca 2011).

Box B.4 Data analysis and recommendation platforms

TripAdvisor is the world’s largest online travel website, helping travellers to research and review travel related services including accommodation providers, restaurants and bars, and sights and attractions. It relies heavily on user-generated content such as ratings, reviews and photos to provide structured search results and recommendations to travellers.

Amazon is an online retailer and marketplace (amongst other things). Amazon uses recommendation algorithms to personalise the shopping experience of each customer – the online store will look radically different for an early 20’s software engineer who reads a lot of sci-fi compared with that for a middle aged mother into thrillers. These recommendations are based on a number of simple elements: what the user has previously purchased, products in their virtual shopping basket, products they have rated and reviewed, and what similar customers have viewed and purchased.

Sources: Linden, Smith and York (2003); Mangalindan (2012); TripAdvisor (2016).

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New products and the creation of digital ecosystems

Some digital intermediaries offer services extending into other parts of the value chain (box B.5). This can create a product ‘ecosystem’, where the intermediary offers a suite of individual product or services that can interact with each other as a complete system.

The movement by digital intermediaries into services beyond matching is in part driven by their access to data. As the intermediary collects better information, it gains a clearer picture of tastes and trends in the marketplace. Sometimes this data is used to sell new information services to existing producers, for example matching ads with specific customers, or helping identify why suppliers may be struggling to sell certain products or services (ACCC 2014b). In other cases, the digital intermediary may use their data to enter the market themselves and offer products and services more efficiently than incumbent suppliers.

Box B.5 Digital intermediaries in other parts of supply chain

Netflix, a provider of on-demand streaming services, offers other services beyond cataloguing and delivering available video content. They take a product that is often owned by another party (such as the movie studios) and provide digitisation and distribution services. Further, the product is not delivered by the movie studio, but by Netflix itself. This new distribution model can influence how the original products are made.

eBay, an e-commerce company, developed the internet payment platform PayPal to provide a degree of protection between market participants – buyers would not have their money transferred until goods were sent, and sellers could be confident to send goods in the knowledge that they would be paid. PayPal also keeps the buyer’s financial information (such as credit card or bank account numbers) private.

Sources: Netflix (2016); PayPal (2016).